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Most organizations have traditionally been organized by function, and most coordination is intrafunctional rather than interfunctional. However, many organizations are finding that they must also manage processes - such as order fulfillment, new product development, and interorganizational supply chain management - that span their separate functional units and that integrate their activities with those of other organizations. These processes are essential to the well-being of organizations in a dynamic competitive environment.In response to this, organizations are deploying large-scale enterprise information systems in order to support operational, tactical, and strategic decision making, along with information management. However, deployment of such information systems has not realized the requisite benefits due to issues such as lack of interoperability among applications due to technological evolution, constant changes to the business processes, evolving organizational structures, inherent complexity in management of distributed knowledge and resources.To ameliorate such issues, a recent technological trend is the adoption of support tools such as Workflow Management Systems (WFMS) and groupware to support coordination between individual and group knowledge worker activities respectively. While WFMSs mostly deal with tasks involving very structured information, groupware tools deal with tasks involving unstructured information. Due to these differences, such tools are used in a fragmented manner, causing information loss. The overall guiding design principles that can be used by such process support systems are minimal, resulting in costly overheads for organizations.This dissertation deals with the problems highlighted above from a organizational process design standpoint. The goal of the dissertation is to provide process designers with guidelines and tools that can assist them in modeling flexible and adaptable processes. The following two research questions are central to the work described in this dissertation: (1) How can organizational processes be designed to be flexible andadaptable in dynamic environments? (2) How can collaborative activities be designed to facilitate integration with individual activities in organizational processes?In this regard, this dissertation reports on the development of a conceptual framework to support design of organizational processes considering both individual and collaboration tasks in a unified manner. A business process is modeled as a problem solving mechanism consisting of a series of steps (also termed as process model, process definition or plan), each of which may be an individual or group activity. The task of designing business processes is considered as the development of an effective plan to solve a business process problem by searching the design space. We employ declarative formalisms from recent advances in Artificial Intelligence (AI) planning to support the task of process design. Similarly, we build on research in the field of Collaboration Engineering (CE), to propose an approach for collaborative task design. The feasibility and benefits of the approach are evaluated by prototyping intelligent build time tools for process design, and utilizing the same in the design of processes such as loan processing, and new drug discovery.

DAEX is a metaheuristic designed to improve the plan quality and the scalability of an encapsulated planning system. DAEX is based on a state decomposition strategy, driven by an evolutionary algorithm, which benefits from the use of a classical planning heuristic to maintain an ordering of atoms within the individuals. The proof of concept is achieved by embedding the domain-independent satisficing YAHSP planner and using the critical path h1 heuristic. Experiments with the resulting algorithm are performed on a selection of IPC benchmarks from classical, cost-based and temporal domains. Under the experimental conditions of the IPC, and in particular with a universal parameter setting common to all domains, DAEYAHSP is compared to the best planner for each type of domain. Results show that DAEYAHSP performs very well both on coverage and quality metrics. It is particularly noticeable that DAEX improves a lot on plan quality when compared to YAHSP, which is known to provide largely suboptimal solutions, making it competitive with state-of-the-art planners. This article gives a full account of the algorithm, reports on the experiments and provides some insights on the algorithm behavior.

abstract: This research introduces Roblocks, a user-friendly system for learning Artificial Intelligence (AI) planning concepts using mobile manipulator robots. It uses a visual programming interface based on block-structured programming to make AI planning concepts easier to grasp for those who are new to robotics and AI planning. Users get to accomplish any desired tasks by dynamically populating puzzle shaped blocks encoding the robot’s possible actions, allowing them to carry out tasks like navigation, planning, and manipulation by connecting blocks instead of writing code. Roblocks has two levels, where in the first level users are made to re-arrange a jumbled set of actions of a plan in the correct order so that a given goal could be achieved. In the second level, they select actions of their choice but at each step only those actions pertaining to the current state are made available to them, thereby pruning down the vast number of possible actions and suggesting only the truly feasible and relevant actions. Both of these levels have a simulation where the user plan is executed. Moreover, if the user plan is invalid or fails to achieve the given goal condition then an explanation for the failure is provided in simple English language. This makes it easier for everyone (especially for non-roboticists) to understand the cause of the failure. / Dissertation/Thesis / Working of Roblocks / Masters Thesis Computer Science 2019

Les systèmes de services contextualisés ont connu un grand essor ces dernières années dans des domaines variés tels que la santé, la logistique ou bien le tourisme. Cette thèse s'intègre dans un projet plus global, nommé E-Tourism, qui vise à réaliser une plateforme de fourniture de services sensibles au contexte à des utilisateurs en situation de mobilité. Le travail de cette thèse se focalise sur la problématique de composition de services web et de leur exécution. La composition de services web permet la réutilisation de services existants afin d'en faire une synthèse répondant au besoin de l'utilisateur. Cette composition se fait en général au niveau de la phase conceptuelle ce qui limite le choix de services potentiels. Cette thèse présente une nouvelle approche de la composition de services Web automatisé et une plateforme d'exécution. Notre approche vise à composer les opérations de services qui répondent aux besoins des utilisateurs mobiles exprimées dans une logique propositionnelle et exécuter le service composé en agrégeant plusieurs services composants. Nous avons proposé une plateforme d'exécution de services et nous avons introduit un nouvel algorithme de planification intégré à cette plateforme. Nous avons défini un contexte basé sur le modèle BPMN. Afin de valider notre modèle sémantique nous avons utilisé une approche de type « model-checking » . Enfin, nous avons réalisé un prototype sous forme d'une plateforme de composition de services et d'exécution automatique en Java. Nous avons implémenté les règles d'inférence et les modèles BPMN en prolog. Enfin, nous avons intégré ces algorithmes dans l'ensemble du système. En perspectives, nous prévoyons d'étendre notre travail actuel et prendre en compte des scénarios plus complexes nécessitant des services web dynamiques. / Recently, distributed computing systems based on context awareness have been proposing in several domains such as healthcare, logistics and tourism. The study described in this thesis is a part of a broader project of E-Tourism system that provides nomad user, context-aware personalized services. The work of this thesis focuses on the issues raised by web service composition and execution. Web service composition brings benefits of reusing existing services to synthesize the new resulting service that meets users needs. The way to create web service composition normally happens at design time, but this limits choices of services. This thesis presents a novel approach of automated web service composition and execution framework. Our approach aims to compose service operations that fulfill mobile users' requirements expressed in propositional logic and execute the resulting service based on aggregating multi service components. In the proposed framework, we have introduced our planning algorithm based on abstract goal states to search and connect to service operations, by mean of service operation annotations, for an abstract plan. The abstract plan is expected for workflow model of sequencing, paralleling and conditioning among service operations. However, the generated workflow is not in an executable form, this is why we perform the transformation of the workflow into an executable business process. To achieve the business process execution, we defined context based BPMN model for mapping the abstract plan to BPMN semantics. We also propose a new validation algorithm and exploited planning-as-model-checking approach to validate the semantic BPMN model whether it is Well-formed and Well-defined BPMN process. Finally, we implemented the automated service composition and execution framework system in Java platform as a proof of concept. We developed the logical composition and, transformation and validation BPMN algorithms written in Prolog. We have integrated these algorithms into the whole system. From the perspective, we plan to extend our current work and take into account more complex user's scenarios that explicitly and implicitly express other pattern controls and we will also consider the scenarios required for stateful web services

Les systèmes de services contextualisés ont connu un grand essor ces dernières années dans des domaines variés tels que la santé, la logistique ou bien le tourisme. Cette thèse s'intègre dans un projet plus global, nommé E-Tourism, qui vise à réaliser une plateforme de fourniture de services sensibles au contexte à des utilisateurs en situation de mobilité. Le travail de cette thèse se focalise sur la problématique de composition de services web et de leur exécution. La composition de services web permet la réutilisation de services existants afin d'en faire une synthèse répondant au besoin de l'utilisateur. Cette composition se fait en général au niveau de la phase conceptuelle ce qui limite le choix de services potentiels. Cette thèse présente une nouvelle approche de la composition de services Web automatisé et une plateforme d'exécution. Notre approche vise à composer les opérations de services qui répondent aux besoins des utilisateurs mobiles exprimées dans une logique propositionnelle et exécuter le service composé en agrégeant plusieurs services composants. Nous avons proposé une plateforme d'exécution de services et nous avons introduit un nouvel algorithme de planification intégré à cette plateforme. Nous avons défini un contexte basé sur le modèle BPMN. Afin de valider notre modèle sémantique nous avons utilisé une approche de type « model-checking » . Enfin, nous avons réalisé un prototype sous forme d'une plateforme de composition de services et d'exécution automatique en Java. Nous avons implémenté les règles d'inférence et les modèles BPMN en prolog. Enfin, nous avons intégré ces algorithmes dans l'ensemble du système. En perspectives, nous prévoyons d'étendre notre travail actuel et prendre en compte des scénarios plus complexes nécessitant des services web dynamiques. / Recently, distributed computing systems based on context awareness have been proposing in several domains such as healthcare, logistics and tourism. The study described in this thesis is a part of a broader project of E-Tourism system that provides nomad user, context-aware personalized services. The work of this thesis focuses on the issues raised by web service composition and execution. Web service composition brings benefits of reusing existing services to synthesize the new resulting service that meets users needs. The way to create web service composition normally happens at design time, but this limits choices of services. This thesis presents a novel approach of automated web service composition and execution framework. Our approach aims to compose service operations that fulfill mobile users' requirements expressed in propositional logic and execute the resulting service based on aggregating multi service components. In the proposed framework, we have introduced our planning algorithm based on abstract goal states to search and connect to service operations, by mean of service operation annotations, for an abstract plan. The abstract plan is expected for workflow model of sequencing, paralleling and conditioning among service operations. However, the generated workflow is not in an executable form, this is why we perform the transformation of the workflow into an executable business process. To achieve the business process execution, we defined context based BPMN model for mapping the abstract plan to BPMN semantics. We also propose a new validation algorithm and exploited planning-as-model-checking approach to validate the semantic BPMN model whether it is Well-formed and Well-defined BPMN process. Finally, we implemented the automated service composition and execution framework system in Java platform as a proof of concept. We developed the logical composition and, transformation and validation BPMN algorithms written in Prolog. We have integrated these algorithms into the whole system. From the perspective, we plan to extend our current work and take into account more complex user's scenarios that explicitly and implicitly express other pattern controls and we will also consider the scenarios required for stateful web services

The problem of domain-independent automated planning has been a topic of research in Artificial Intelligence since the very beginnings of the field. Due to the desire not to rely on vast quantities of problem specific knowledge, the most widely adopted approach to automated planning is search. The topic of this thesis is the development of methods for achieving effective search control for domain-independent optimal planning through the construction of admissible heuristics. The particular planning problem considered is the so called “classical” AI planning problem, which makes several restricting assumptions. Optimality with respect to two measures of plan cost are considered: in planning with additive cost, the cost of a plan is the sum of the costs of the actions that make up the plan, which are assumed independent, while in planning with time, the cost of a plan is the total execution time – makespan – of the plan. The makespan optimization objective can not, in general, be formulated as a sum of independent action costs and therefore necessitates a problem model slightly different from the classical one. A further small extension to the classical model is made with the introduction of two forms of capacitated resources. Heuristics are developed mainly for regression planning, but based on principles general enough that heuristics for other planning search spaces can be derived on the same basis. The thesis describes a collection of methods, including the hm, additive hm and improved pattern database heuristics, and the relaxed search and boosting techniques for improving heuristics through limited search, and presents two extended experimental analyses of the developed methods, one comparing heuristics for planning with additive cost and the other concerning the relaxed search technique in the context of planning with time, aimed at discovering the characteristics of problem domains that determine the relative effectiveness of the compared methods. Results indicate that some plausible such characteristics have been found, but are not entirely conclusive.

Planning is a challenging research area since the early days of Artificial Intelligence. The planning problem is the task of finding a sequence of actions leading an agent from a given initial state to a desired goal state. Whereas classical planning adopts restricting assumptions such as complete knowledge about the initial state and deterministic action effects, in real world scenarios we often have to face incomplete knowledge and non-determinism. Classical planning languages and algorithms do not take these facts into account. So, there is a strong need for formal languages describing such non-classical planning problems on the one hand and for (declarative) methods for solving these problems on the other hand.In this thesis, we present the action language Kc, which is based on flexible action languages from the knowledge representation community and extends these by useful concepts from logic programming.We define two basic semantics for this language which reflect optimistic and secure (i.e. sceptical) plans in presence of incomplete information or nondeterminism. These basic semantics are furthermore extended to planning with action costs, where each action can have an assigned cost value. Here, we address optimal plans as well as plans which stay within a certain overall cost limit.Next, we develop efficient (i.e. polynomial) transformations from planning problems described in our language Kc to disjunctive logic programs which are then evaluated under the so-called Answer Set Semantics. In this context, we introduce a general new method for problem solving in Answer Set Programming (ASP) which takes the genuine "guess and check" paradigm in ASP into account and allows us to integrate separate "guess" and "check" programs into a single logic program. Based on these methods, we have implemented the planning system DLVK. We discuss problem solving and knowledge representation in Kc using DLVK by means of several examples. The proposed methods and the DLVK system are also evaluated experimentally and compared against related approaches. Finally, we present a practical application scenario from the area of design and monitoring of multi-agent systems. As we will see, this monitoring approach is not restricted to our particular formalism. / Austrian Science Funds (FWF)

運用語義網本體論來描述網路服務，實現網路服務的自動發現、調用和組合已經被證實是有效的。人工智慧規劃技術就是運用此技術描述網路服務來達到自動化網路服務組合。OWL-S支援使用OWL來描述網路服務的前提與效果，而在OWL的規則描述語言方面，則可以使用SWRL。本論文是以OntoComposer規劃工具為基礎，發展一套前置處理器來簡化其使用，讓使用者不需具備人工智慧規劃描述語言及語義網路服務描述等知識，只要尋找到符合需求之網路服務後，就可以自動轉換成支持條件分支圖規劃器之輸入文件，並在設定目標後進行規劃組合，最後讓組合之複合網路能夠在執行引擎上正確執行。 / Using Semantic Web ontologies to describe Web Services has proven to be effective for automatic service discovery, invokcation and composition. AI planning techniques have been employed to automate the composition of Web Services in this way. OWL-S supports the description of the preconditions and effects of a web service using OWL statements, and SWRL is the language for expressing OWL Rules. OntoComposer is an AI planning based tool for Combining-GraphPlan, an extension for GraphPlan so that supports condition branching. This thesis presents a preprocessor for OntoComposer to simplify its input task so that the user does not have to learn the AI Planning description language and knowledge of the semantic web service description. Just look to meet the demand of web services, our preprocessor will translate them to support branch planning for the input file. After setting the targets the OntoComposer will compose some component web services to a complex web service. Finally, let the composition of web services on the execution engine the correct execution.